As growing dependence on wind and solar energy brings about new challenges in both maximizing energy generation and ensuring the stability of grids due to the intermittent nature by virtue of dependence on variable atmospheric conditions, optimization of hybrid solar-wind plant output is achieved through the present study by means of a DE algorithm for maximum energy yield enhancement and grid robustness. The approach includes a simulation of a small hybrid energy system, which consists of a 10 m2 solar panel and three wind turbines, each with a capacity of 2 kW, over a period of 24 h. Using real meteorological data in the form of solar irradiance and wind speed profiles, the differential evolution (DE) algorithm minimizes two most important parameters: tilt angle of solar panels from 0 to 90 degrees and the spacing of the wind turbines, variable from 5 to 50 m. The objective function is to maximize energy output in total and minimize hour-by-hour power oscillations, a surrogate for grid stability. The results indicate that the optimized configuration with tilt angle 15.23° and turbine spacing of 35.67 m produces a total of 135.82 kWh, up 12.7% from the baseline (120.45 kWh at tilt angle 30° and 10 m spacing). Moreover, the stability penalty, expressed as the sum of hourly output differences, reduces from 48.73 to 42.19, reflecting better grid compatibility. These results underscore the potential of DE as a successful method for the optimization of renewable energy, with a real application to harmonize energy production and stability in hybrid systems. This research supports more efficient and trustworthy renewable grids and contributes to sustainable energy infrastructures transition.